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Image of - Remote Sensing Image Classification In R | Hardcover
Remote Sensing Image Classification In R | Hardcover

Remote Sensing Image Classification In R | Hardcover

by Kamusoko C

This book offers an introduction to remotely sensed image processing and classification in R using machine learning algorithms. It also provides a concise and practical reference tutorial, which equips readers to immediately start using the software platform and R packages for image processing and classification.This book is divided into five chapters. Chapter 1 introduces remote sensing digital image processing in R, while chapter 2 covers pre-processing. Chapter 3 focuses on image transformation, and chapter 4 addresses image classification. Lastly, chapter 5 deals with improving image classification.R is advantageous in that it is open source software, available free of charge and includes several useful features that are not available in commercial software packages. This book benefits all undergraduate and graduate students, researchers, university teachers and other remote- sensing practitioners interested in the practical implementation of remote sensing in R.

Highlights

  • binding-icon

    9789811380112

    ISBN:

  • binding-icon

    Kamusoko C

    Author:

  • binding-icon

    189

    Pages:

  • binding-icon

    210 gm

    Weight:

  • langauage-icon

    English

    Language:

  • date-icon

    2019

    Year:

  • edition-icon

    N/A

    Edition:

  • binding-icon

    Hardcover

    Binding:

₹11317

₹14146

This book offers an introduction to remotely sensed image processing and classification in R using machine learning algorithms. It also provides a concise and practical reference tutorial, which equips readers to immediately start using the software platform and R packages for image processing and classification.This book is divided into five chapters. Chapter 1 introduces remote sensing digital image processing in R, while chapter 2 covers pre-processing. Chapter 3 focuses on image transformation, and chapter 4 addresses image classification. Lastly, chapter 5 deals with improving image classification.R is advantageous in that it is open source software, available free of charge and includes several useful features that are not available in commercial software packages. This book benefits all undergraduate and graduate students, researchers, university teachers and other remote- sensing practitioners interested in the practical implementation of remote sensing in R.

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